LAUSR

The thermal behaviour of buildings in transient conditions is established by the temperature evolution of the external environment. Determining the thermal evolution of buildings is of crucial importance for building energy design, as well as for energetic performance evaluation. Building energy performance evaluation and calculation of energy use for space heating and cooling can be carried out by several methods of various degrees of complexity and accuracy. These methods are implemented in such simulation codes as NBLSD, Il DOE-II, ENERGY PLUS and others. In order to comply with the Energy Performance of Buildings Directive (EPBD), the studies and research in this field start from the Directive 91/2002/CE and subsequently lead to the EN ISO 13790:2007. The latter proposes a thermal model for a building composed of five resistances and one capacity, called R5C1, and also offers its dynamic solution with a simple hourly computational model. The present paper suggests the solution and dynamic simulation of the R5C1 model and an evaluation of its use in building energy design. Finally, a case study regarding a typical average day in June in Catania (Sicily, Italy) is presented. The implemented model and the relative simulation results have confirmed the advantages of such a solution and have been validated for some modules of the CONPHOEBUS scrl Research Building in Catania. The proposed model has the advantage of a small number of parameters (5 thermal resistances and 1 thermal capacity) and has a simple formulation and then requires low computational resources. Furthermore, this model allows the correct estimation of the user profile with few and not sufficiently precise input data. Due to the above listed properties the proposed model was adopted by the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) for an extensive energy consumption simulation campaign involving 5000 buildings in Italy (a campaign of measurements on 20,000 buildings planned for 2017) for the calculation of statistical consumption data for public buildings.